Depth sensing can be used for a variety of different applications, such as assisting in the navigation of autonomous vehicles and other robots, building a 3D model of a person, object, or scene, or inserting virtual objects into a live scene (sometimes called augmented reality). Passive depth sensing has many advantages over active sensing techniques such as sonar, radar, or structured light. For instance, passive depth sensing allows for greater range, higher spatial resolution, and a wider spectrum. But conventional passive depth sensing techniques tend to be computationally intensive and often take a powerful computer several seconds or minutes to generate depth information. These computational requirements limit the adoption of conventional passive depth sensing techniques.